POS0661 A RADIOMICS MODEL DERIVED FROM T1-WEIGHTED IMAGES FOR EVALUATING STRUCTURAL LESIONS OF THE SACROILIAC JOINT USING LOW-DOSE CT AS THE REFERENCE STANDARD
Authors: M. Zheng, G. Zhu, D. Chen, Q. Xiao, C. Ye, T. Lei, C. Pan, S. Miao, L. Ye
Journal: Annals of the Rheumatic Diseases (2023)

<h3>Background</h3> Detection of structural lesions of the sacroiliac joint (SIJ) in patients with chronic low back pain is crucial for the diagnosis and classification of axial spondyloarthritis (axSpA). With MRI becoming a part of a routine diagnostic approach of axSpA, the question about the value of T1-weighted images (T1WI) evaluating structural lesions raised. <h3>Objectives</h3> To construct and validate a radiomics model based on T1WI to assess SIJ structural lesions in patients with suspected axSpA. <h3>Methods</h3> A total of 266 patients with clinical suspicion of axSpA between December 2016 and January 2022 were enrolled. Structural lesions were assessed by low-dose CT (ldCT) and MRI, respectively. Radiomics features, extracted from SIJ T1WI, were included to generate the radiomics model. Performance of the radiomics model was evaluated by the receiver operating characteristic curve. Point-biserial correlation analysis was used to interpret the associations between the radiomics features and structural lesions. <h3>Results</h3> Structural lesions were found in 122 of 187 patients (65.2%) in the training cohort and 52 of 79 patients (65.8%) in the validation cohort. Using ldCT as the gold standard, the area under the curves (AUCs) of the radiomics model and MRI experienced raters were 0.82 (95% CI: 0.76, 0.88) vs 0.73 (95% CI: 0.67, 0.79) in the training cohort, and 0.82 (95% CI: 0.72, 0.91) vs 0.74 (95% CI: 0.66, 0.83) in the validation cohort. The seven radiomics features included showed significant correlation with various structural lesions (<i>P</i> all &lt;0.05). Among them, Wavelet.LHL_firstorder_90Percentile showed the strongest association with fat lesion (r = 0.48, <i>P</i>&lt;0.05). <h3>Conclusion</h3> The radiomics analysis with T1WI could effectively detect SIJ structural lesions and each radiomics feature was correlated with different structural lesions significantly, which might inform radiomic-based applications for axSpA intelligent diagnosis. <h3>References</h3> [1]van der Linden S, Valkenburg HA, Cats A. Evaluation of diagnostic criteria for ankylosing spondylitis. A proposal for modification of the New York criteria. Arthritis Rheum. 1984;27(4):361-8. [2]Bakker PA, van den Berg R, Lenczner G, Thevenin F, Reijnierse M, Claudepierre P, et al. Can we use structural lesions seen on MRI of the sacroiliac joints reliably for the classification of patients according to the ASAS axial spondyloarthritis criteria? Data from the DESIR cohort. Ann Rheum Dis. 2017;76(2):392-8. [3]Poddubnyy D, Gaydukova I, Hermann KG, Song IH, Haibel H, Braun J, et al. Magnetic resonance imaging compared to conventional radiographs for detection of chronic structural changes in sacroiliac joints in axial spondyloarthritis. The Journal of rheumatology. 2013;40(9):1557-65. [4]Ye L, Liu Y, Xiao Q, Dong L, Wen C, Zhang Z, et al. MRI compared with low-dose CT scanning in the diagnosis of axial spondyloarthritis. Clin Rheumatol. 2020;39(4):1295-303. [5]Diekhoff T, Hermann KG, Greese J, Schwenke C, Poddubnyy D, Hamm B, et al. Comparison of MRI with radiography for detecting structural lesions of the sacroiliac joint using CT as standard of reference: results from the SIMACT study. Ann Rheum Dis. 2017;76(9):1502-8. <h3>Acknowledgements:</h3> NIL. <h3>Disclosure of Interests</h3> None Declared.